A GLRT approach to data-aided timing acquisition in UWB radios - Part I: Algorithms
IEEE Transactions on Wireless Communications, ISSN: 1536-1276, Vol: 4, Issue: 6, Page: 2956-2967
2005
- 92Citations
- 1Usage
- 6Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations92
- Citation Indexes92
- 92
- CrossRef57
- Usage1
- Abstract Views1
- Captures6
- Readers6
Article Description
Realizing the great potential of impulse radio communications depends critically on the success of timing acquisition. To this end, optimum data-aided (DA) timing offset estimators are derived in this paper based on the maximum likelihood (ML) criterion. Specifically, generalized likelihood ratio tests (GLRTs) are employed to detect an ultrawideband (UWB) waveform propagating through dense multipart) and to estimate the associated timing and channel parameters in closed form. Capitalizing on the pulse repetition pattern, the GLRT boils down to an amplitude estimation problem, based on which closed-form timing acquisition estimates can be obtained without invoking any line search. The proposed algorithms only employ digital samples collected at a low symbol rate, thus reducing considerably the implementation complexity and acquisition time. Analytical acquisition performance bounds and corroborating simulations are also provided. © 2005 IEEE.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=18444402052&origin=inward; http://dx.doi.org/10.1109/twc.2005.858356; http://ieeexplore.ieee.org/document/1545871/; http://xplorestaging.ieee.org/ielx5/7693/32988/01545871.pdf?arnumber=1545871; https://digitalcommons.mtu.edu/michigantech-p/11171; https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=30473&context=michigantech-p
Institute of Electrical and Electronics Engineers (IEEE)
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know